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Information Disclosure, Security, and Data Quality

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Recent Trends and Future Technology in Applied Intelligence (IEA/AIE 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10868))

Abstract

Data sharing is important to interested parties for mining trends and patterns in designing data-driven decision-making systems. However, sharing raw data creates severe problems like identity theft or personal information leakage such as disclosure of illness of a specific person. This study analyzed results from an Adaptive Differential Privacy (ADiffP) algorithm that satisfies \(\varepsilon \)-differential privacy for publishing sanitized data. The algorithm was tested with two different data sets to measure its robustness by comparing other existing works. The results obtained from the proposed algorithm show that the sanitized data preserves the same pattern as the raw data. Additionally, classification accuracies for sanitized data are also promising.

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Notes

  1. 1.

    https://www.statcan.gc.ca/.

  2. 2.

    Non-synthetically.

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Authors and Affiliations

  1. School of Computer Science, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada

    A. N. K. Zaman, Charlie Obimbo & Rozita A. Dara

Authors
  1. A. N. K. Zaman
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  2. Charlie Obimbo
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  3. Rozita A. Dara
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Corresponding author

Correspondence to A. N. K. Zaman .

Editor information

Editors and Affiliations

  1. University of Regina, Regina, SK, Canada

    Malek Mouhoub

  2. University of Regina, Regina, SK, Canada

    Samira Sadaoui

  3. Concordia University, Montreal, QC, Canada

    Otmane Ait Mohamed

  4. Texas State University, San Marcos, TX, USA

    Moonis Ali

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Zaman, A.N.K., Obimbo, C., Dara, R.A. (2018). Information Disclosure, Security, and Data Quality. In: Mouhoub, M., Sadaoui, S., Ait Mohamed, O., Ali, M. (eds) Recent Trends and Future Technology in Applied Intelligence. IEA/AIE 2018. Lecture Notes in Computer Science(), vol 10868. Springer, Cham. https://doi.org/10.1007/978-3-319-92058-0_75

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  • DOI: https://doi.org/10.1007/978-3-319-92058-0_75

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92057-3

  • Online ISBN: 978-3-319-92058-0

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